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Funding Acknowledgements Type of funding sources: None. Introduction Integrated care is effective in reducing all-cause mortality in patients with atrial fibrillation (AF) in primary care. Although this overall effect is undisputed, some individual patients may benefit more than others. The aim of this post-hoc analysis of the cluster-randomized ALL-IN trial, performed in primary care, is to explore heterogeneity of the effect of integrated AF care. Methods A model was developed and validated to predict the outcome all-cause mortality using the CHA2DS2-VASc items as predictors. The hazard ratio and absolute risk reduction were plotted as a function of this predicted mortality risk using the ALL-IN data. The interaction between treatment and predicted risk was tested for significance to identify treatment heterogeneity. Results Among 1,240 AF patients included in the ALL-IN trial (median 77 years (range 65-104), 49.4% female) the model for predicted mortality showed a c-statistic of 0.72 [95% CI 0.66-0.78] with good calibration. The hazard ratio for the intervention across all risk levels ranged from 0.28 to 0.81, yet without a significant interaction effect (p for interaction=0.93). However, the absolute risk reduction of integrated AF care was greatest in patients with the highest predicted risk. Conclusion Independent of the risk of mortality related to comorbidities, all AF patients benefit from integrated care in the primary care setting. Importantly, on an absolute scale, the effect is greatest in patients with a high-risk profile of comorbidities. These results stress the need for integrated AF care, including patients at high-risk of mortality and with multimorbidity.

BackgroundMeasuring the performance of models that predict individualized treatment effect is challenging because the outcomes of two alternative treatments are inherently unobservable in one patient. The C-for-benefit was proposed to measure discriminative ability. However, measures of calibration and overall performance are still lacking. We aimed to propose metrics of calibration and overall performance for models predicting treatment effect.MethodsSimilar to the previously proposed C-for-benefit, we defined observed pairwise treatment effect as the difference between outcomes in pairs of matched patients with different treatment assignment. We redefined the E-statistics, the cross-entropy, and the Brier score into metrics for measuring a model’s ability to predict treatment effect. In a simulation study, the metric values of deliberately “perturbed models” were compared to those of the data-generating model, i.e., “optimal model”. To illustrate these performance metrics, different modeling approaches for predicting treatment effect are applied to the data of the Diabetes Prevention Program: 1) a risk modelling approach with restricted cubic splines; 2) an effect modelling approach including penalized treatment interactions; and 3) the causal forest.ResultsAs desired, performance metric values of “perturbed models” were consistently worse than those of the “optimal model” (Eavg-for-benefit≥0.070 versus 0.001, E90-for-benefit≥0.115 versus 0.003, cross-entropy-for-benefit≥0.757 versus 0.733, Brier-for-benefit≥0.215 versus 0.212). Calibration, discriminative ability, and overall performance of three different models were similar in the case study. The proposed metrics were implemented in a publicly available R-package “HTEPredictionMetrics”.ConclusionThe proposed metrics are useful to assess the calibration and overall performance of models predicting treatment effect.

Humans are exposed to combinations of chemicals. In cumulative risk assessment (CRA), regulatory bodies such as the European Food Safety Authority consider dose addition as a default and sufficiently conservative approach. The principle of dose addition was confirmed previously for inducing craniofacial malformations in zebrafish embryos in binary mixtures of chemicals with either similar or dissimilar modes of action (MOAs).In this study, we explored a workflow to select and experimentally test multiple compounds as a complex mixture with each of the compounds at or below its no observed adverse effect level (NOAEL), in the same zebrafish embryo model.Selection of candidate compounds that potentially induce craniofacial malformations was done usingA final selection of eight compounds was examined in the zebrafish embryo model, and craniofacial malformations were observed in embryos exposed to each of the compounds, thus confirming the developmental toxicity as predicted by theThis case study of a complex mixture inducing craniofacial malformations in zebrafish embryos shows that dose addition can adequately predicted the cumulative effect of a mixture of multiple substances at low doses, irrespective of the (expected) MOA. The applied workflow may be useful as an approach for CRA in general. https://doi.org/10.1289/EHP9888.

In this prospective longitudinal study, Coronary Artery Calcium (CAC) scores determined before the start of whole breast irradiation were compared with those determined 7 years afterwards. The aim was to examine whether the use of a breath-hold (BH) technique is associated with less increase of CAC scores.Changes in CAC scores were analysed in 87 breast cancer patients. The results of the following groups were compared: patients receiving right (R) or left-sided radiotherapy using free breathing (L-FB) with those receiving left-sided radiotherapy with BH (L-BH). We compared the changes of CAC scores between these groups over time, testing the hypothesis that a significantly reduced increase of calcium scores is observed when using BH.For L-BH cases, when compared with L-FB cases, for overall as well as for Left Anterior Descending coronary artery (LAD) CAC scores, we noted significantly less increased CAC scores (p 0.01). This effect of BH was even more striking in the group with CAC scores0 at baseline. The attenuated increase over time of CAC scores in the L-BH group was robust to correction for age and statin use (p 0.05).After a median follow-up of 7.4 years, we found significantly less increased CAC scores when using BH. This is a relevant finding since higher levels of CAC scores are associated with higher probabilities of coronary artery events. Moreover, it underlines the rationale for the use of BH in left-sided whole breast irradiation.

Highlights • Scoring the tumor-stroma ratio is a simple and reproducible method. • Tumor-stroma ratio and response to neoadjuvant chemoradiotherapy are correlated. • Stroma-low tumors are likely to respond better to neoadjuvant chemoradiotherapy., Background and purpose With currently available techniques, the prediction of pathologic complete response after neoadjuvant chemoradiotherapy is insufficient. The tumor-stroma ratio (TSR) has proven to be a predictor of survival for several types of cancer, including esophageal. The aim of this study was to investigate the value of TSR in predicting pathologic response after neoadjuvant chemoradiotherapy in esophageal cancer patients. Materials and methods Patients with esophageal adenocarcinoma or squamous cell carcinoma who received neoadjuvant chemoradiotherapy followed by a resection were selected. Haematoxylin and eosin (H&E) stained sections of diagnostic biopsies were collected and TSR was independently assessed by two investigators. Patients were categorized in stroma-low (≤50% stroma) and stroma-high (>50% stroma) groups for further analyses. The tumor regression grade (TRG) was assessed on H&E stained sections of the resected primary tumor to determine pathologic response. Results A total of 94 patients were included in this study, of which 76 patients were categorized as stroma-low and 18 as stroma-high. Forty-two (45%) patients had a major pathologic response (TRG 1–2), whereas 52 (55%) were considered non-responders. After adjustment for gender, tumor type, cT-status and differentiation grade, patients with a stroma-high tumor showed a higher chance of no response compared to patients with a stroma-low tumor (OR 3.57, 95%CI 1.03–12.31, P = 0.04). Conclusion TSR showed to have the potential to aid in the prediction of pathologic response in esophageal cancer patients receiving neoadjuvant chemoradiotherapy. Larger validation studies are necessary before implementing this method in daily practice.

Background The SYNTAX score II 2020 (SSII-2020), which was derived and externally validated from randomized trials, was designed to predict death following percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) in patients with three-vessel disease and/or left main disease. We aimed to investigate its value in identifying the safest modality of revascularization in a non-randomized setting. Methods Five-year mortality was assessed in 7362 patients with three-vessel disease and/or left main disease enrolled in a Japanese PCI/CABG registry. New-generation drug eluting stents and imaging guidance became the default PCI strategy during enrolment of the last cohort. The discriminative ability of the SSII-2020 for 5-year mortality was assessed using Harrell's C statistic (C-index). Agreement between observed and predicted rates of all-cause mortality following either PCI or CABG and treatment benefit (absolute risk difference) for this outcome were assessed by calibration plots. Results The SSII-2020 had helpful discrimination (C-index = 0.72) and good calibration (intercept = −0.11, slope = 0.92) for 5-year mortality. The absolute risk difference in mortality between CABG and PCI (treatment benefit) was well calibrated when the whole population was grouped into quarters according to the predicted absolute risk difference of 5-year mortality. The observed differences in survival in favor of CABG were 4.2% (0.1 to 8.2%, log-rank p=0.05) and 8.5% (3.8 to 13.2%, log-rank p Conclusions The SSII-2020 is well able to predict death at 5 years – and the mortality difference between PCI and CABG, and therefore has the potential to support decision making on revascularization in patients with three-vessel disease and/or left main coronary artery disease. Funding Acknowledgement Type of funding sources: None.

© 2021 The Authors. Published by Elsevier GmbH. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., Data generated by the rapidly evolving human biomonitoring (HBM) programmes are providing invaluable opportunities to support and advance regulatory risk assessment and management of chemicals in occupational and environmental health domains. However, heterogeneity across studies, in terms of design, terminology, biomarker nomenclature, and data formats, limits our capacity to compare and integrate data sets retrospectively (reuse). Registration of HBM studies is common for clinical trials; however, the study designs and resulting data collections cannot be traced easily. We argue that an HBM Global Registry Framework (HBM GRF) could be the solution to several of challenges hampering the (re)use of HBM (meta)data. The aim is to develop a global, host-independent HBM registry framework based on the use of harmonised open-access protocol templates from designing, undertaking of an HBM study to the use and possible reuse of the resulting HBM (meta)data. This framework should apply FAIR (Findable, Accessible, Interoperable and Reusable) principles as a core data management strategy to enable the (re)use of HBM (meta)data to its full potential through the data value chain. Moreover, we believe that implementation of FAIR principles is a fundamental enabler for digital transformation within environmental health. The HBM GRF would encompass internationally harmonised and agreed open access templates for HBM study protocols, structured web-based functionalities to deposit, find, and access harmonised protocols of HBM studies. Registration of HBM studies using the HBM GRF is anticipated to increase FAIRness of the resulting (meta)data. It is also considered that harmonisation of existing data sets could be performed retrospectively. As a consequence, data wrangling activities to make data ready for analysis will be minimised. In addition, this framework would enable the HBM (inter)national community to trace new HBM studies already in the planning phase and their results once finalised. The HBM GRF could also serve as a platform enhancing communication between scientists, risk assessors, and risk managers/policy makers. The planned European Partnership for the Assessment of Risk from Chemicals (PARC) work along these lines, based on the experience obtained in previous joint European initiatives. Therefore, PARC could very well bring a first demonstration of first essential functionalities within the development of the HBM GRF.

Supplemental Digital Content is available in the text., Background: There are many clinical prediction models (CPMs) available to inform treatment decisions for patients with cardiovascular disease. However, the extent to which they have been externally tested, and how well they generally perform has not been broadly evaluated. Methods: A SCOPUS citation search was run on March 22, 2017 to identify external validations of cardiovascular CPMs in the Tufts Predictive Analytics and Comparative Effectiveness CPM Registry. We assessed the extent of external validation, performance heterogeneity across databases, and explored factors associated with model performance, including a global assessment of the clinical relatedness between the derivation and validation data. Results: We identified 2030 external validations of 1382 CPMs. Eight hundred seven (58%) of the CPMs in the Registry have never been externally validated. On average, there were 1.5 validations per CPM (range, 0–94). The median external validation area under the receiver operating characteristic curve was 0.73 (25th–75th percentile [interquartile range (IQR)], 0.66–0.79), representing a median percent decrease in discrimination of −11.1% (IQR, −32.4% to +2.7%) compared with performance on derivation data. 81% (n=1333) of validations reporting area under the receiver operating characteristic curve showed discrimination below that reported in the derivation dataset. 53% (n=983) of the validations report some measure of CPM calibration. For CPMs evaluated more than once, there was typically a large range of performance. Of 1702 validations classified by relatedness, the percent change in discrimination was −3.7% (IQR, −13.2 to 3.1) for closely related validations (n=123), −9.0 (IQR, −27.6 to 3.9) for related validations (n=862), and −17.2% (IQR, −42.3 to 0) for distantly related validations (n=717; P

Background Patients with melanoma and negative sentinel nodes (SNs) have varying outcomes, dependent on several prognostic factors. Considering all these factors in a prediction model might aid in identifying patients who could benefit from a personalized treatment strategy. The objective was to construct and validate a nomogram for recurrence and melanoma‐specific mortality (MSM) in patients with melanoma and negative SNs. Methods A total of 3220 patients with negative SNs were identified from a cohort of 4124 patients from four EORTC Melanoma Group centres who underwent sentinel lymph node biopsy. Prognostic factors for recurrence and MSM were studied with Cox regression analysis. Significant factors were incorporated in the models. Performance was assessed by discrimination (c‐index) and calibration in cross‐validation across the four centres. A nomogram was developed for graphical presentation. Results There were 3180 eligible patients. The final prediction model for recurrence and the calibrated model for MSM included three independent prognostic factors: ulceration, anatomical location and Breslow thickness. The c‐index was 0·74 for recurrence and 0·76 for the calibrated MSM model. Cross‐validation across the four centres showed reasonable model performance. A nomogram was developed based on these models. One‐third of the patients had a 5‐year recurrence probability of 8·2 per cent or less, and one‐third had a recurrence probability of 23·0 per cent or more. Conclusion A nomogram for predicting recurrence and MSM in patients with melanoma and negative SNs was constructed and validated. It could provide personalized estimates useful for tailoring surveillance strategies (reduce or increase intensity), and selection of patients for adjuvant therapy or clinical trials., Could personalize care

ObjectiveTo assess whether the Prediction model Risk Of Bias ASsessment Tool (PROBAST) and a shorter version of this tool can identify clinical prediction models (CPMs) that perform poorly at external validation.Study Design and SettingWe evaluated risk of bias (ROB) on 102 CPMs from the Tufts CPM Registry, comparing PROBAST to a short form consisting of six PROBAST items anticipated to best identify high ROB. We then applied the short form to all CPMs in the Registry with at least 1 validation and assessed the change in discrimination (dAUC) between the derivation and the validation cohorts (n=1,147).ResultsPROBAST classified 98/102 CPMS as high ROB. The short form identified 96 of these 98 as high ROB (98% sensitivity), with perfect specificity. In the full CPM registry, 529/556 CPMs (95%) were classified as high ROB, 20 (4%) low ROB, and 7 (1%) unclear ROB. Median change in discrimination was significantly smaller in low ROB models (dAUC −0.9%, IQR −6.2%–4.2%) compared to high ROB models (dAUC −11.7%, IQR −33.3%–2.6%; pConclusionHigh ROB is pervasive among published CPMs. It is associated with poor performance at validation, supporting the application of PROBAST or a shorter version in CPM reviews.What is newHigh risk of bias is pervasive among published clinical prediction modelsHigh risk of bias identified with PROBAST is associated with poorer model performance at validationA subset of questions can distinguish between models with high and low risk of bias

This report presents the results of a feasibility study for improving transparency and accessibility of the models implemented in the Monte Carlo Risk Assessment (MCRA) web platform for assessing the risk of combined exposure to multiple chemicals via multiple exposure routes. It provides an overview of the history and current use of the web platform and its scientific and regulatory context. The technical infrastructure of the current MCRA web platform and the modular design of the various models of MCRA are described. Based on selected user stories, user requirements are established, and suggestions are made for possible designs of an open source collection of MCRA models. Technical options are listed for code organisation, programming language, interfacing and containerisation, data organisation, storage and licensing.Also, the role of the MCRA web platform is discussed. The report ends with a suggested approach and next steps, includinga discussion on the need for a governance structure for sustainable development of Open MCRA.

Focus on risks to human health and the environment from combined exposure to multiple chemicals ("mixture risk assessment") has increased in the last couple of decades. There has been a rise in awareness and concern in the community, especially concerning unintentional environmental exposure to unknown chemical mixtures. The Horizon 2020 project EuroMix has developed methodologies and tools for mixture risk assessment with a focus on component-based approach where substances are grouped based on toxicological considerations. Dose addition is used as the model for calculating the combined toxicity of mixture components. The methodology is anchored in the Adverse Outcome Pathway (AOP) concept, which provides a structured basis for e.g. grouping substances into assessment groups and identifying and collecting relevant toxicity data. The aim of this paper is to describes development of the methodology for mixture risk assessment and to provide detailed methodology for problem formulation, use of AOP networks for development of tiered testing strategies and grouping of substances, as well as considerations for use of dose addition methodology.

The number of anthropogenic chemicals, manufactured, by-products, metabolites and abiotically formed transformation products, counts to hundreds of thousands, at present. Thus, humans and wildlife are exposed to complex mixtures, never one chemical at a time and rarely with only one dominating effect. Hence there is an urgent need to develop strategies on how exposure to multiple hazardous chemicals and the combination of their effects can be assessed. A workshop, “Advancing the Assessment of Chemical Mixtures and their Risks for Human Health and the Environment” was organized in May 2018 together with Joint Research Center in Ispra, EU-funded research projects and Commission Services and relevant EU agencies. This forum for researchers and policy-makers was created to discuss and identify gaps in risk assessment and governance of chemical mixtures as well as to discuss state of the art science and future research needs. Based on the presentations and discussions at this workshop we want to bring forward the following Key Messages: • We are at a turning point: multiple exposures and their combined effects require better management to protect public health and the environment from hazardous chemical mixtures. • Regulatory initiatives should be launched to investigate the opportunities for all relevant regulatory frameworks to include prospective mixture risk assessment and consider combined exposures to (real-life) chemical mixtures to humans and wildlife, across sectors. • Precautionary approaches and intermediate measures (e.g. Mixture Assessment Factor) can already be applied, although, definitive mixture risk assessments cannot be routinely conducted due to significant knowledge and data gaps. • A European strategy needs to be set, through stakeholder engagement, for the governance of combined exposure to multiple chemicals and mixtures. The strategy would include research aimed at scientific advancement in mechanistic understanding and modelling techniques, as well as research to address regulatory and policy needs. Without such a clear strategy, specific objectives and common priorities, research, and policies to address mixtures will likely remain scattered and insufficient. Keywords: Chemical mixtures, Environmental chemicals, Combined exposure, Mixture risk assessment, Risk management

Mixtures of substances to which humans are exposed may lead to cumulative exposure and health effects. To study their effects, it is first necessary to identify a cumulative assessment group (CAG) of substances for risk assessment or hazard testing. Excluding substances from consideration before there is sufficient evidence may underestimate the risk. Conversely, including everything and treating the inevitable uncertainties using conservative assumptions is inefficient and may overestimate the risk, with an unknown level of protection. An efficient, transparent strategy is described to retain a large group, quantifying the uncertainty of group membership and other uncertainties. Iterative refinement of the CAG then focuses on adding information for the substances with high probability of contributing significantly to the risk. Probabilities can be estimated using expert opinion or derived from data on substance properties. An example is presented with 100 pesticides, in which the retain step identified a single substance to target refinement. Using an updated hazard characterisation for this substance reduced the mean exposure estimate from 0.43 to 0.28 μg kg-bw−1 day−1 and reduced the 99.99th percentile exposure from 24.9 to 5.1 μg kg-bw−1 day−1. Other retained substances contributed little to the risk estimates, even after accounting for uncertainty.

International audience; A model and data toolbox is presented to assess risks from combined exposure to multiple chemicals using probabilistic methods. The Monte Carlo Risk Assessment (MCRA) toolbox, also known as the EuroMix toolbox, has more than 40 modules addressing all areas of risk assessment, and includes a data repository with data collected in the EuroMix project. This paper gives an introduction to the toolbox and illustrates its use with examples from the EuroMix project. The toolbox can be used for hazard identification, hazard characterisation, exposure assessment and risk characterisation. Examples for hazard identification are selection of substances relevant for a specific adverse outcome based on adverse outcome pathways and QSAR models. Examples for hazard characterisation are calculation of benchmark doses and relative potency factors with uncertainty from dose response data, and use of kinetic models to perform in vitro to in vivo extrapolation. Examples for exposure assessment are assessing cumulative exposure at external or internal level, where the latter option is needed when dietary and non-dietary routes have to be aggregated. Finally, risk characterisation is illustrated by calculation and display of the margin of exposure for single substances and for the cumulation, including uncertainties derived from exposure and hazard characterisation estimates.

Pesticide residues in food can lead to harmful toxic effects when exposed. Some of these compounds have a common Mode of Action and thus elicit a similar biological response. This paper considers the triazoles, a class of widely used fungicides exhibiting the same short-term (acute) and long-term (chronic) response in humans. We examined Belgian pesticide residue data from 2011-2014 and coupled these with the results of the Belgian food consumption survey of 2004. Cumulative probabilistic risk assessment was done using the Monte Carlo Risk Assessment 8.0 web application. The European Food Safety Authority (EFSA) published a guidance document that proposes both optimistic and pessimistic scenarios for dietary exposure assessment. Other than those two, a third, more balanced, scenario was simulated and showed an exposure right in between the EFSA scenarios. In the optimistic scenario, the foods with the highest measured residues in the residue data contributed the most to the total health risk. In the balanced and pessimistic scenarios, the highest contribution to the total health risk was made by active ingredients with a high sampling rate and/or a high consumption rate. No significant trends were observed in the health risk through 2011 to 2014, and the exposure distribution showed no health risks for the extreme consumers, with one exception in 2012.

Populations are exposed to mixtures of pesticides through their diet on a daily basis. The question of which substances should be assessed together remains a major challenge due to the complexity of the mixtures. In addition, the associated risk is difficult to characterise. The EuroMix project (European Test and Risk Assessment Strategies for Mixtures) has developed a strategy for mixture risk assessment. In particular, it has proposed a methodology that combines exposures and hazard information to identify relevant mixtures of chemicals belonging to any cumulative assessment group (CAG) to which the European population is exposed via food. For the purposes of this study, food consumption and pesticide residue data in food and drinking water were obtained from national surveys in nine European countries. Mixtures of pesticides were identified by a sparse non-negative matrix underestimation (SNMU) applied to the specific liver steatosis effect in children from 11 to 15 years of age, and in adults from 18 to 64 years of age in nine European countries. Exposures and mixtures of 144 pesticides were evaluated through four different scenarios: (1) chronic exposure with a merged concentration dataset in the adult population, (2) chronic exposure with country-specific concentration datasets in the adult population, (3) acute exposure with a merged concentration dataset in the adult population, and (4) chronic exposure with a merged concentration dataset in the paediatric population. The relative potency factors of each substance were calculated to express their potency relative to flusilazole, which was chosen as the reference compound. The selection of mixtures and the evaluation of exposures for each country were carried out using the Monte Carlo Risk Assessment (MCRA) software. Concerning chronic exposure, one mixture explained the largest proportion of the total variance for each country, while in acute exposure, several mixtures were often involved. The results showed that there were 15 main pesticides in the mixtures, with a high contribution of imazalil and dithiocarbamate. Since the concentrations provided by the different countries were merged in the scenario using merged concentration data, differences between countries result from differences in food consumption behaviours. These results support the approach that using merged concentration data to estimate exposures in Europe seems to be realistic, as foods are traded across European borders. The originality of the proposed approach was to start from a CAG and to integrate information from combined exposures to identify a refined list of mixtures with fewer components. As this approach was sensitive to the input data and required significant resources, efforts should continue regarding data collection and harmonisation among the different aspects within the pesticides regulatory framework, and to develop methods to group substances and mixtures to characterise the risk.

In the context of the second framework partnership agreement between the National Institute for Public Health and the Environment of the Netherlands (RIVM) and the European Food Safety Authority (EFSA)acute cumulative dietary exposure assessments were performed for two cumulative assessment groups (CAGs) of pesticidesthat affect the nervous system: pesticides associated with brain and/or erythrocyte AChE inhibition (CAG-NAN, 47 pesticides) and pesticides associated with functional alterations of the motor division (CAG-NAM, 100 pesticides). The exposure assessments used pesticide monitoring data collected by Member States under their official monitoring programmes in 2014, 2015 and 2016 and individual food consumption data from ten populations of consumers from different countries and from different age groups. Exposure estimates were obtained for each group of pesticides by means of a 2-dimensional Monte Carlo simulation, which was implemented in the Monte Carlo Risk Assessment (MCRA) software.The scope of the assessment and the parameters to be used for cumulative exposure assessment were discussed and agreed by the Standing Committee on Plants, Animals, Food and Feed (SC PAFF). Based on those discussions, a very conservative tier I modelling approach and a refined, but still conservative tier II modelling approach were used. In these assessments, common risk assessment practice was followed and the cumulative exposure was calculated as total margin of exposure (MOET) at the 50th, 90th, 95th, 99th and 99.9th percentiles of the exposure distribution. Five sensitivity analyses aiming to address major uncertainties were performed. The exposure estimates obtained in this report are used in EFSA's scientific report on the cumulative dietary risk characterisation of pesticides that have acute effects on the nervous system.

Risk assessment of chemicals occurring in our diet is commonly performed for single chemicals without considering exposure to other chemicals. We performed a case study on risk assessment of combined dietary exposure to chemicals from different regulatory silos, i.e. pesticides (PPRs), persistent organic pollutants (POPs) and food additives (FAs). Chemicals were grouped into the cumulative assessment group (CAG) liver steatosis using a component-based approach. Based on literature, the CAG included 144 PPRs, 49 POPS and 7 FAs for which concentration data were available. For each silo, chronic combined dietary exposure was assessed for adults and children of nine European countries following the most commonly used exposure methodologies in Europe and by using a relative potency factor approach. For risk characterization, a Margin of Exposure (MOE) was calculated. To overarch the risk across silos, a normalised combined margin of exposure (nMOET) approach was proposed. This case study demonstrated that risk assessment of combined exposure to chemicals can be performed within regulatory silos. It also highlighted important differences in the conservatism of exposure scenarios, the derivation of point of departures and the subsequent acceptable MOEs between the silos. To overarch the risk despite these differences, a nMOET approach can be used.

Through their diet, populations are exposed to mixtures of chemicals which can cause health diseases. Due to the complexity of mixtures, the question of which substances should be assessed together...

In specific contract No 4 issued under the framework agreement GP/EFSA/PRAS/2014/02 to Support the Regulatory Implementation of Cumulative Exposure Assessment of Pesticides, EFSA requested RIVM and its subcontractor Wageningen University & Research, Biometris to propose a data model organising the information related to specific elements of cumulative dietary exposure assessment for pesticides, which were toxicological information (i.e., cumulative assessment groups and substance potency information related to the specific effect), the authorisation status of plant protection products over time (per pesticide/commodity combination at national level), the use frequency of plant protection products over time (per pesticide/commodity combination at national level), the MRL in force over time, extrapolation rules according to the ad-hoc EC guidance, processing data (mean and individual values), and residue definitions for monitoring and risk assessment (possibly related to groups of commodities). The data model proposed in this report standardises how the data elements relate to one another, and allows the automation of main regulatory modelling assumptions, settings and default values when information is missing. The proposed data model is compatible with the format of data and coding rules of the EFSA standard sample description (SSD) and the EFSA DWH.

The need for improved tools to estimate the cumulative and aggregate exposure to compounds such as plant protection products (PPPs) is recognised in the EU Regulation 1107/2009. A new model has been developed to estimate the exposure within a population to single compounds or compounds within a Cumulative Action Group, considering dietary and non-dietary sources and multiple exposure routes. To test the model a field study was carried out in Italy with operators applying tebuconazole fungicides, with measurements of dermal exposure collected. Whole urine samples were collected and analysed to provide values for the absorbed dose of tebuconazole, with duplicate diet samples collected and analysed as a measure of dietary exposures. The model provided predicted values of exposure for combined dietary and non-dietary routes of exposures which were compared to the measured absorbed dose values based on urinary analysis. The model outputs provided mean daily exposure values of 1.77 (± 1.96) µg a.s./kg BW which are comparable to measured mean values from the biomonitoring field study of 1.73 (± 1.31) µg a.s./kg BW. To supplement the limited measurement data available, comparisons against other models were also made and found to be comparable.

Every day, we are exposed to multiple chemicals by several routes of exposure: diet, inhalation and dermal contact. Until recently, risk assessment is mostly performed separately for each chemical, considering only a single route of exposure. However, this simplified risk assessment does not take into account the effect that chemicals may have on each other and their effect on the same target organ. According to EU Regulation, EFSA is responsible to establish the methodology for combined exposure to multiple pesticides. Recently, EFSA has published the outline of the methodology on the EFSA website, including four EFSA opinions on how based on their toxicological profile and EFSA guidance on how to perform the exposure assessment. EFSA started grouping pesticides into cumulative assessment groups based on their toxicological profile for all pesticides affecting the nervous system and all pesticides affecting the thyroid gland. EFSA noticed that relevant information on the toxicity of the chemical is not always available. Consequently, EFSA applied a precautionary principle in their grouping and it was noticed that refinements are possible when data on toxicity becomes available. To this end, the new European funded project EuroMix will apply several in-silico and in-vitro tools to mixtures of chemicals that can affect the liver, the endocrine system, and the development stage. A number of test systems, including omics technology and classic toxicological testing, will be explored. The most promising tests for mixtures will be verified against results from animal studies. Once validated, the tests will be used to collect information needed to refine the risk assessment. Data and models will become available in a web-based platform for all European countries and stakeholders.

Background The value of conventional prognostic factors is unclear in the era of multimodal treatment for oesophageal cancer. This study aimed to quantify the impact of neoadjuvant chemoradiotherapy (nCRT) and surgery on well established prognostic factors, and to develop and validate a prognostic model. Methods Patients treated with nCRT plus surgery were included. Multivariable Cox modelling was used to identify prognostic factors for overall survival. A prediction model for individual survival was developed using stepwise backward selection. The model was internally validated leading to a nomogram for use in clinical practice. Results Some 626 patients who underwent nCRT plus surgery were included. In the multivariable model, only pretreatment cN category and ypN category were independent prognostic factors. The final prognostic model included cN, ypT and ypN categories, and had moderate discrimination (c-index at internal validation 0·63). Conclusion In patients with oesophageal or oesophagogastric cancer treated with nCRT plus surgery, overall survival can best be estimated using a prediction model based on cN, ypT and ypN categories. Predicted survival according to this model showed only moderate correlation with observed survival, emphasizing the need for new prognostic factors to improve survival prediction.

Long-term exposures to dioxins (PCCD/F and dioxin-like PCBs) and ochratoxin A were calculated using food consumption data of the European concise database combined with concentration data of the Netherlands (NL) using a deterministic approach. To refine these assessments, exposures were also calculated using three long-term exposure models, observed individual means (OIM), Iowa State University Foods (ISUF), and betabinomial-normal (BBN) models, combined with individual food consumption data of NL. BBN and ISUF correct the variation in long-term exposure for the within-person variation, whereas OIM calculates the mean exposure over the days in the food consumption survey. Exposures obtained with the concise database were highest, and those obtained with OIM higher than with BBN and ISUF. Contribution of the major sources of exposure differed between the concise database and the three models. Given the constraints of the concise database, exposures obtained with this database should be interpreted as a first tier assessment. Preferably, refined assessments using models that correct the variation in long-term exposure for the within-person variation combined with individual food consumption data and national concentration data should be used to assess the long-term exposure. We recommend the use of BBN since it can model exposure distributions that depend on covariates.

ObjectiveHealth logos are introduced to distinguish foods with ‘healthier’ nutrient composition from regular foods. In the present study, we evaluated the effects of changed food compositions according to health logo criteria on the intake of saturated fat, sugar and sodium in a Dutch population of young adults.DesignFoods in the Dutch food composition table were evaluated against nutrient criteria for logo eligibility. Three replacement scenarios were compared with the nutrient intake ‘as measured’ in the Dutch consumption survey. The foods not complying with health logo criteria were replaced either by ‘virtual’ foods exactly complying with the health logo criteria, with real 2007 market shares (scenario I) and 100 % market shares (scenario II), or by existing similar foods with a composition that already complied with the health logo criteria (scenario III).ResultsThe percentage reduction in nutrient intake with the current 2007 market shares of ‘health logo foods’ was −2·5 % for SFA, 0 % for sodium and −1 % for sugar. With a 100 % market share these reductions would be −10 % for SFA, −4 % for sodium and −6 % for sugar. This may lead to a reduction of −40 % for SFA, −23 % for sodium and −36 % for sugar in the most optimal replacement scenario.ConclusionsWith ‘health logo foods’, available in 2007 and current consumption patterns, small reductions can be achieved for SFA and sugar. For additional reductions, lowering the fat/sodium content of meat (products) towards health logo criteria and drinks without sugar towards limits far below health logo criteria would be the most effective reformulation strategy.

In this paper, we present an approach to format national food consumption data at raw agricultural commodity (RAC) level. In this way, the data is both formatted in a harmonised way given the comparability of RACs between countries, and suitable to assess the dietary exposure to chemicals analysed in RACs at a European level. In this approach, consumption data needs to be converted to edible part of RAC (e-RAC) level using a RAC conversion database. To subsequently use this data in exposure assessments, both e-RACs and RACs analysed in chemical control programmes should be classified via a uniform system. Furthermore, chemical concentrations in RACs may need to be converted to e-RAC level using processing factors. To illustrate the use of this approach, we describe how the Dutch RAC conversion database was used to convert consumption data of four national consumption surveys to e-RAC level, and the use of the FAO/WHO Codex Classification system of Foods and Animal Feeds to harmonise the classification. We demonstrate that this approach works well for pesticides and glycoalkaloids, and is an essential step forward in the harmonisation of risk assessment procedures within Europe when addressing chemicals analysed in RACs by all national food control systems.

The interest in holistic considerations in the area of food safety is increasing. Risk managers may face the problem that reducing the risk of one compound may increase the risk of another compound. An example is the potential increase in mycotoxin levels due to a reduced use of fungicides in crop production. The Integrated Probabilistic Risk Assessment (IPRA) model was used to compare the estimated health impacts on humans caused by crops contaminated with the fungicides spiroxamine (SPI) and tebuconazole (TEB) or with the mycotoxins deoxynivalenol (DON) and zearalenone (ZEA). The IPRA model integrates a distribution characterising the exposure of individuals with a distribution characterising the susceptibility of individuals towards toxic effects. Its outcome, a distribution of Individual Margins of Exposure (IMoE), served as basis to perform comparisons of compounds, effects, countries, and population groups. Based on the available data and the assumptions made, none of the four compounds was found to have impact on human health in the addressed scenarios. The IMoE distributions were located as follows: DON < TEB = ZEA < SPI, showing DON to be the compound with the highest potential for negative health impacts. The presented approach can help risk managers to prioritise risk-reduction measures.

The current study aims at estimating the dietary intake of PBDEs in the Netherlands and evaluating the resultant risk. Dietary intake was estimated using results of PBDE analyses in Dutch food products from 2003/2004 and consumption data of the third Dutch National Food Consumption Survey (1997/1998). Assuming that non-detects represent levels of half the detection limit, the median long-term intake of the Dutch population of the sum of five major PBDEs (namely PBDEs 47, 99, 100, 153+154) is 0.79 ng/kg body weight bw/day (P97.5: 1.62 ng/kg bw/day). When non-detects are considered as zeros the values are 0.53 (median) and 1.34 (P97.5) ng/kg bw/day. Environmental concentrations of PBDEs in Europe are expected to decline in the near future because of the ban on penta- and octaBDE technical products. However, it will take at least a decade before this will result in lower PBDE concentrations in food products. Hence, a regular monitoring program for PBDEs is recommended. A risk evaluation at the most sensitive endpoints of BDE 99 carried out in this paper indicates that, although the long-term exposure to BDE 99 is well below the human exposure threshold level for neurodevelopmental toxicity, it may be close to that for reproductive toxicity. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA.

A model is presented which allows to quantify the simultaneous distribution of the exposure to two compounds, for example a health-risk and a health promoting compound. The model considers the total dietary intake, and can be used as a first step to study the effects on the balance between risks and benefits following changes in the consumption pattern. The exposure is modelled separately for intake probabilities using a betabinomial model, and for intake amounts using a lognormal model, and these parts are afterwards integrated by Monte Carlo simulation. The model is illustrated using the risk¿benefit case of dioxins and the omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). High concentrations of both the health adverse compounds and the health promoting compounds are simultaneously present in fatty fish. Calculated exposures were compared with intake limits: the adequate intake for EPA + DHA and the tolerable daily intake (TDI) for dioxins. We estimate the probability that dioxin exposure is below TDI, the probability that EPA + DHA exposure is above the adequate intake, and the probability that both conditions occur simultaneously. We also model the dependence of these probabilities on age. In the studied population the exposure to both compounds is almost completely below the limits. A scenario study in which meat consumption was replaced by fatty fish consumption shows an increase in the fraction of the population with the recommended intake of EPA + DHA, however also the fraction of the population exceeding the TDI for dioxins is increased. For the example scenario the optimal amount of fatty fish consumption is derived.

OBJECTIVE: We assessed the effects of an intervention aimed at increasing the consumption of fruits and vegetables on plasma folate and homocysteine concentrations. METHODS: Seventy-one healthy non-smoking women (mean +/- SD 41 +/- 4 y of age) were randomized to an intervention or a control group. Participants in the intervention group (n = 36) received weekly packets containing fruits and vegetables free of charge and were asked to consume a daily amount of >/=200 g of vegetables and two pieces of fruit (the Dutch recommended intake level) over a period of 1 mo. Control subjects did not receive any intervention. RESULTS: Compared with the control group, reported fruit and vegetable intakes in the intervention group increased by 133 g/d (95% confidence interval [CI] 87-179, P < 0.001) for fruits and juice and 64 g/d (95% CI 37-91, P < 0.001) for vegetables and estimated folate intake from fruits and vegetables increased by 40 mug/d (95% CI 22-58, P < 0.001). However, no effect was observed on plasma folate concentrations (intervention effect 0.3 nmol/L, 95% CI -1.8 to 2.8, P = 0.77) or homocysteine concentrations (intervention effect 0.26 mumol/L, 95% CI -0.34 to 0.87, P = 0.39). CONCLUSION: The results suggest that 4 wk of increased fruit and vegetable consumption to the recommended amounts may be insufficient to change plasma folate and homocysteine concentrations.

Pesticide risk assessment is hampered by worst-case assumptions leading to overly pessimistic assessments. On the other hand, cumulative health effects of similar pesticides are often not taken into account. This paper describes models and a web-based software system developed in the European research project ACROPOLIS. The models are appropriate for both acute and chronic exposure assessments of single compounds and of multiple compounds in cumulative assessment groups. The software system MCRA (Monte Carlo Risk Assessment) is available for stakeholders in pesticide risk assessment at mcra.rivm.nl. We describe the MCRA implementation of the methods as advised in the 2012 EFSA Guidance on probabilistic modelling, as well as more refined methods developed in the ACROPOLIS project. The emphasis is on cumulative assessments. Two approaches, sample-based and compound-based, are contrasted. It is shown that additional data on agricultural use of pesticides may give more realistic risk assessments. Examples are given of model and software validation of acute and chronic assessments, using both simulated data and comparisons against the previous release of MCRA and against the standard software DEEM-FCID used by the Environmental Protection Agency in the USA. It is shown that the EFSA Guidance pessimistic model may not always give an appropriate modelling of exposure.

Exposures to plant protection products (PPPs) are assessed using risk analysis methods to protect public health. Traditionally, single sources, such as food or individual occupational sources, have been addressed. In reality, individuals can be exposed simultaneously to multiple sources. Improved regulation therefore requires the development of new tools for estimating the population distribution of exposures aggregated within an individual. A new aggregate model is described, which allows individual users to include as much, or as little, information as is available or relevant for their particular scenario. Depending on the inputs provided by the user, the outputs can range from simple deterministic values through to probabilistic analyses including characterisations of variability and uncertainty. Exposures can be calculated for multiple compounds, routes and sources of exposure. The aggregate model links to the cumulative dietary exposure model developed in parallel and is implemented in the web-based software tool MCRA. Case studies are presented to illustrate the potential of this model, with inputs drawn from existing European data sources and models. These cover exposures to UK arable spray operators, Italian vineyard spray operators, Netherlands users of a consumer spray and UK bystanders/residents. The model could also be adapted to handle non-PPP compounds.

This study evaluates the attitudes and perspectives of different stakeholder groups (agricultural producers, pesticide manufacturers, trading companies, retailers, regulators, food safety authorities, scientists and NGOs) towards the concepts of cumulative and aggregate exposure assessment of pesticides by means of qualitative in-depth interviews (n = 15) and a quantitative stakeholder survey (n = 65). The stakeholders involved generally agreed that the use of chemical pesticides is needed, primarily for meeting the need of feeding the growing world population, while clearly acknowledging the problematic nature of human exposure to pesticide residues. Current monitoring was generally perceived to be adequate, but the timeliness and consistency of monitoring practices across countries were questioned. The concept of cumulative exposure assessment was better understood by stakeholders than the concept of aggregate exposure assessment. Identified pitfalls were data availability, data limitations, sources and ways of dealing with uncertainties, as well as information and training needs. Regulators and food safety authorities were perceived as the stakeholder groups for whom cumulative and aggregate pesticide exposure assessment methods and tools would be most useful and acceptable. Insights obtained from this exploratory study have been integrated in the development of targeted and stakeholder-tailored dissemination and training programmes that were implemented within the EU-FP7 project ACROPOLIS.

In this paper two models present in the computational tool Monte Carlo Risk Assessment (MCRA) were compared for assessing the usual intake of lead in five countries. For this, we used national food consumption data organised according to the format of the European Food Safety Authority (EFSA) Comprehensive database and a single lead concentration database in which analysed commodities were organised according to EFSA's Standard Sampling Description (SSD) system. This meant that both input data were coded according to the hierarchical FoodEx1 classification system. We demonstrate that the naïve Observed Individual Means model resulted in more conservative estimates of the exposure in the right tail of the exposure distribution compared to a refined usual intake model, the LogisticNormal–Normal model. With MCRA, the usual intake could be estimated with both models using food consumption and concentration data that were coded according to the hierarchical FoodEx1 classification system demonstrating that this tool can be used in EFSA's data environment. Additionally, the computational tool has functionalities 1) to check the input data quality by presenting detailed information about these data around a specified percentile of exposure and 2) to decide whether the use of a more refined usual intake model is appropriate.

The present document has been produced and adopted by the bodies identified above as author(s). In accordance with Article 36 of Regulation (EC) No 178/2002, this task has been carried out exclusively by the author(s) in the context of a grant agreement between the European Food Safety Authority and the author(s). The present document is published complying with the transparency principle to which the Authority is subject. It cannot be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors.

The present document has been produced and adopted by the bodies identified above as author(s). In accordance with Article 36 of Regulation (EC) No 178/2002, this task has been carried out exclusively by the author(s) in the context of a grant agreement between the European Food Safety Authority and the author(s). The present document is published complying with the transparency principle to which the Authority is subject. It cannot be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors.

Background/purpose The number of dietary exposure assessment studies focussing on children is very limited. Children are however a vulnerable group due to their higher food consumption level per kg body weight. Therefore, the EXPOCHI project aims [1] to create a relational network of individual food consumption databases in children, covering different geographical areas within Europe, and [2] to use these data to assess the usual intake of lead, chromium, selenium and food colours. Methods EXPOCHI includes 14 food consumption databases focussed on children (1-14 y old). The data are considered representative at national/regional level: 14 regions covering 13 countries. Since the aim of the study is to perform long-term exposure assessments, only data derived from 24 hr dietary recalls and dietary records recorded on at least two non-consecutive days per individual were included in the dietary exposure assessments. To link consumption data and concentration data of lead, chromium and selenium in a standardised way, categorisation of the food consumption data was based on the food categorisation system described within the SCOOP Task report 3.2.11. For food colours, the food categorisation system specified in the Council Directive 94/36/EC was used. Conclusion The EXPOCHI project includes a pan-European long-term exposure assessment of lead, chromium, selenium and food colours among children living in 13 different EU countries. However, the different study methods and designs used to collect the data in the different countries necessitate an in-depth description of these different methods and a discussion about the resulting limitations.

Within the EFSA Article 36 project “European Tool Usual Intake” (ETUI) a workshop was organised in May 2010 where the different available models to calculate usual intake were presented and discussed. This report integrates the workshop background document, the presentations given by experts, and the discussions during the workshop. The purpose of the workshop was to evaluate existing statistical methods for estimating usual intake with respect to a number of criteria, so that the performance of each method on each criterion will be well understood after the workshop. The outcome of the workshop allows choices to be made for a European Tool Usual Intake, to be implemented in the remainder of the project. A starting document was provided to the participants of the workshop with up-to-date information on methods, data and criteria, as a basis for discussion. It was apparent from the workshop that there is not one optimal model for all cases, rather a toolbox approach is suitable. The choice of the most appropriate model has to be fine-tuned case by case. Criteria to be considered are related to data availability and data pre-processing (e.g. compatibility of existing data formats, need to handle complicating factors like food code conversion, left-censored data, processing factors, brand loyalty, pooling over multiple datasets), the appropriateness of modelling assumptions for frequencies and amounts modelling (e.g. level of conservatism, additivity assumption and data transformations, the need to model intake as a function of covariates, correlations), the usefulness to combine survey and food frequency questionnaire data, the need to model single food intake or diet-aggregated intake, the need to evaluate uncertainties, and the usefulness of implementations. For the short term, case studies will be performed based on issues relevant for EFSA panels. Results from the workshop and possibilities of using models to calculate usual intake were recently discussed during the 5th meeting of the EFSA Expert group on food consumption data. Currently only few EU Member States use this kind of models but there is a lot of interest in gaining experience with the usual intake modelling. Several requests were received concerning the possibility of having more information about the ETUI project and even the organisation of a future training. In conclusion, this interim report is considered by EFSA to be a good review of the different models used and presents the main challenges related to the use of these techniques. Its publication could be useful to those who want to start using this kind of methodology

Previous EFSA exposure assessments of selenium have been based on limited data and a more detailed assessment was considered important. As part of the EXPOCHI project, long-term dietary exposure to selenium in young children living in 12 different European countries was assessed. National or regional individual food consumption data from 14 different food consumption databases were used together with selenium concentration data in food collected in eight Member States. Food consumption data were all categorised according to a harmonised system to allow for linkage with selenium concentration data in a standardised way. Two approaches were used to calculate long-term exposure to selenium: the observed individual means (OIM) and the beta-binomial normal (BBN) approach. The results showed differences in exposure between countries based on food consumption patterns and decreased exposure with increased age. Young children in the upper bound scenario commonly exceeded the tolerable upper intake level of 5 μg/kg bw per day. However, current results should be interpreted with caution since they do not necessarily represent the actual selenium exposure in the respective country. To improve reliability, consumption and occurrence results should be linked at more detailed levels, local variations in selenium concentrations explored and handling of long-term exposure calculations refined for all types of data distributions. 1 EFSA-Q-2010-00786. Accepted for Publication on 12 May 2010. 2 Current affiliation is „National Institute of Public Health and the Environment (RIVM), Bilthoven, The Netherlands‟ Long-term dietary exposure to selenium in children living in Europe